1. Field of the Invention
The present invention relates to a method for identifying an object image by way of differentiating an object image from a background image shown on a picture and more particularly to a method for identifying an object image of, for instance, humans, vehicles, vegetables, etc. in a picture.
2. Prior Art
Conventionally for the Texture Analysis, a Fourier transformation is utilized to analyze a two-dimensional grayscale picture. The Fourier transformation for the picture generally is used to analyze the state of the surface of the object image shown in the picture. In such an analysis, a picture is divided into square regions, and a Fourier transformation is performed on the image data of the respective square regions, and crystal lattice directions, defects, etc. in the object image are analyzed based upon the obtained phase.
In this case, since a Fourier transformation is performed on the square regions, the obtained phase becomes a vertical or horizontal directional vector of the square region. Accordingly, when, with this method, recognizing an object image with an un-specific form in a picture, there is a need for an even greater calculation to determine the normal line direction of the outline portion of the object image. Moreover, since the picture is divided into squares, depending on the position of the boundary of the picture and the position where the square is arranged, the normal vector of the object image may not be obtained accurately. In order to reduce this disadvantage, a window function is applied on the outer portion of the square region so as to lighten the weight. However, this results in a longer calculation time.
On the other hand, in image processing in real time, when recognizing an indefinite shaped moving object image such as an individual (human), a differential image or phase difference of the current image and the prior image (one frame prior to the current image) is utilized. This conventional method is used to estimate the number of people, etc. based on the area of the region by way of detecting a density difference more than a set level from the differential image, etc. However, in this method, since the recognition of the object image is determined based on area size, it is unavoidable to incorrectly recognize the object image. For instance, it may recognize one large person as two people, or two small people moving in the same direction side by side as one person, etc.
In addition, in a single screen taken by a camera installed tilted at an angle at a predetermined location or by a camera with a wide-angle lens, etc., depending on the position where the object is located when its image is taken, the outline portion of the object image will be shown differently even though the same object is taken. Thus, according to the differential image processing etc., the area difference becomes larger, and it is difficult to judge whether it is the same object image or not.